A generalized framework to predict continuous scores from medical ordinal labels

Many variables of interest in clinical medicine, like disease severity, are recorded using discrete ordinal categories such as normal/mild/moderate/severe. These labels are used to train and evaluate disease severity prediction models. However, ordinal categories represent a simplification of an underlying continuous severity spectrum. Using continuous scores instead of ordinal categories is more sensitive to detecting small changes in disease severity over time. Here, we present a generalized framework that accurately predicts continuously valued variables using only discrete ordinal labels during model development. We found that for three clinical prediction tasks, models that take the ordinal relationship of the training labels into account outperformed conventional multi-class classification models. Particularly the continuous scores generated by ordinal classification and regression models showed a significantly higher correlation with expert rankings of disease severity and lower mean squared errors compared to the multi-class classification models. Furthermore, the use of MC dropout significantly improved the ability of all evaluated deep learning approaches to predict continuously valued scores that truthfully reflect the underlying continuous target variable. We showed that accurate continuously valued predictions can be generated even if the model development only involves discrete ordinal labels. The novel framework has been validated on three different clinical prediction tasks and has proven to bridge the gap between discrete ordinal labels and the underlying continuously valued variables

Photography-based taxonomy is inadequate, unnecessary, and potentially harmful for biological sciences

The question whether taxonomic descriptions naming new animal species without type specimen(s) deposited in collections should be accepted for publication by scientific journals and allowed by the Code has already been discussed in Zootaxa (Dubois & Nemésio 2007; Donegan 2008, 2009; Nemésio 2009a–b; Dubois 2009; Gentile & Snell 2009; Minelli 2009; Cianferoni & Bartolozzi 2016; Amorim et al. 2016). This question was again raised in a letter supported by 35 signatories published in the journal Nature (Pape et al. 2016) on 15 September 2016. On 25 September 2016, the following rebuttal (strictly limited to 300 words as per the editorial rules of Nature) was submitted to Nature, which on 18 October 2016 refused to publish it. As we think this problem is a very important one for zoological taxonomy, this text is published here exactly as submitted to Nature, followed by the list of the 493 taxonomists and collection-based researchers who signed it in the short time span from 20 September to 6 October 2016

Genome-wide association identifies novel ROP risk loci in a multiethnic cohort

We conducted a genome-wide association study (GWAS) in a multiethnic cohort of 920 at-risk infants for retinopathy of prematurity (ROP), a major cause of childhood blindness, identifying 1 locus at genome-wide significance level (p < 5×10-8) and 9 with significance of p < 5×10-6 for ROP ≥ stage 3. The most significant locus, rs2058019, reached genome-wide significance within the full multiethnic cohort (p = 4.96×10-9); Hispanic and European Ancestry infants driving the association. The lead single nucleotide polymorphism (SNP) falls in an intronic region within the Glioma-associated oncogene family zinc finger 3 (GLI3) gene. Relevance for GLI3 and other top-associated genes to human ocular disease was substantiated through in-silico extension analyses, genetic risk score analysis and expression profiling in human donor eye tissues. Thus, we identify a novel locus at GLI3 with relevance to retinal biology, supporting genetic susceptibilities for ROP risk with possible variability by race and ethnicity

Variability in plus disease diagnosis using single and serial images

The purpose of this study is to assess changes in ROP diagnosis in single and serial retinal images. Cohort study Cases of retinopathy of prematurity recruited from the i-ROP consortium evaluated by seven graders Seven ophthalmologists reviewed both single and three consecutive serial retinal images from 15 ROP cases, and severity was assigned as plus, pre-plus, or none. Imaging data was acquired during routine ROP screening from 2011 to 2015 and a reference standard diagnosis was established for each image. A secondary analysis was performed using the i-ROP deep learning system to assign a vascular severity score (VSS) to each image, ranging from 1-9, with 9 being most severe disease. This score has been previously demonstrated to correlate with the International Classification of ROP. Mean plus disease severity was calculated by averaging 14 labels per image in serial and single images to decrease noise. Grading severity of ROP as defined by plus, pre-plus, or no ROP Assessment of serial retinal images changed the grading severity for >50% of the graders, though there was wide variability. Cohen’s kappa ranged from 0.29 to 1.0, which showed a wide range of agreement from slight to perfect by each grader. Changes in grading of serial retinal images was noted more commonly in cases of pre-plus disease. The mean severity in cases with a diagnosis of plus disease and no disease did not change between single and serial images. The ROP vascular severity score demonstrated good correlation with the range of expert classifications of plus disease, and overall agreement with the mode class (p=0.001). The VSS correlated with mean plus disease severity by expert diagnosis (correlation coefficient 0.89). More aggressive graders tended to be influenced by serial images to increase the severity of their grading. The vascular severity score also demonstrated agreement with disease progression across serial images which progressed to pre-plus and plus disease. Clinicians demonstrated variability in ROP diagnosis when presented with both single and serial images. The use of deep learning as a quantitative assessment of plus disease has the potential to standardize ROP diagnosis and treatment

Multivariate discrimination among cryptic mites of the genus Androlaelaps (Acari: Mesostigmata: Laelapidae) parasitic of sympatric akodontine rodents (Cricetidae: Sigmodontinae) in northeastern Argentina: possible evidence of host switch followed by speciation, with the description of two new species

Laelapids are among the most common ectoparasites of rodents. Currently, it is under discussion whether there is a single polixenous species that parasites a variety of hosts, or whether there are cryptic species highly host specific. Herein, multivariate morphometric analyses of cryptic sympatric laelapids of the genus Androlaelaps allowed us to identify different species. These species are specific of their akodontine hosts, Akodon montensis and Thaptomys nigrita, in localities situated in northeastern Argentina. In addition, we analyzed similar laelapids associated with the akodontines Deltamys kempi and Akodon cursor. Using principle component analyses we differentiated four laelapid species, each one host specific, independent of sympatry of the hosts, and without geographical variation. From these four species, we described two new species (Androlaelaps navonae n. sp. and Androlaelaps wingei n. sp.). We determined the four species based on a range of variations in several characters, mainly size. These four laelapid species belong to the Androlaelaps rotundus species group, specific to akodontines. These species are very similar among them but differ from the remainder species of the group by their small size, distance between j6 setae similar to the distance between the z5 setae, strong ventral setae, opisthogaster with 13 pairs of strong setae (one close to the distal margin of epigynal shield), and anal shield wider than long. Further studies will elucidate whether they constitute a new laelapid genus. Phylogenetic and ecological factors influencing host-specificity are discussed, and we propose that host colonization could have taken place by host switching of a single laelapid species among rodent species, followed by speciation.Fil: Lareschi, Marcela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Centro de Estudios Parasitológicos y de Vectores. Universidad Nacional de La Plata. Facultad de Ciencias Naturales y Museo. Centro de Estudios Parasitológicos y de Vectores; ArgentinaFil: Galliari, Carlos Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Centro de Estudios Parasitológicos y de Vectores. Universidad Nacional de La Plata. Facultad de Ciencias Naturales y Museo. Centro de Estudios Parasitológicos y de Vectores; Argentin